RBIF-0103-G1Probability and Statistics Prof. M. Partensky Brandeis University - Spring 2003 Group Project Using Statistics and Mathematica to Analyze Body.

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Presentation transcript:

RBIF-0103-G1Probability and Statistics Prof. M. Partensky Brandeis University - Spring 2003 Group Project Using Statistics and Mathematica to Analyze Body Temperatures Vaishali Khamamkar Timothy Foley

Human Body Temperature as a Predictor of Ovulation Tracking body temperature is part of an effective, low-tech. process that is used to predict ovulation Many couples have difficulties in getting pregnant There is a large body of online data posted, where women share their experiences, to help themselves and each other We thank them, and wish to treat their personal data with the utmost respect

Technical Data and Measurements The posted data is based upon daily measurements of a women’s body termperature A Basal Body Temperature thermometer is used, accurate to 1/10° F The captured data shows a statistical Time Series

Results with Mathematica We gathered days of BBT data for 12 women We plotted that data using: –ListPlot [ ], MultipleListPlot [ ] We used an Epilog to show –Target Ovulation Date (Vertical Line) –Cover Line – Avg. Body Temp. (Horizontal Line) 12 Graphs are displayed (Cyan Background)

Data Manipulation Smoothing of Data We wanted to smooth out the data in our results A Rolling Mean metric is added, that calculates each day’s temperature as the average of: –Previous day’s BBT temperature –Current day BBT temperature –Next day’s BBT temperature 12 new graphs are shown (light-green background): –Blank lines shown original plotted time series –Purple lines show smoothed Rolling Mean time series

Results – BBT and Ovulation All women show a rise in BBT values of 0.5°- 2.0° F. within one day of ovulation We also note a BBT plateau, followed by a second rise in BBT, 3-5 days after ovulation More information on this process is available at :

Concluding Remarks We found several interesting areas of study related to body temperature We learned things that we did not know or expect Our knowledge of Statistics was broadened by this project We found Mathematica to be a powerful and useful tool (once we got the hang of it!)